metadpy.utils.type2_SDT_simuation#
- metadpy.utils.type2_SDT_simuation(d: float = 1, noise: Union[float, List[float]] = 0.2, c: float = 0, nRatings: int = 4, nTrials: int = 500) Tuple[ndarray, ndarray][source]#
Type 2 SDT simulation with variable noise.
- Parameters
- d
Type 1 dprime.
- noise
Standard deviation of noise to be added to type 1 internal response for type 2 judgment. If noise is a 1 x 2 vector then this will simulate response-conditional type 2 data where noise = [sigma_rS1, sigma_rS2].
- c
Type 1 criterion.
- c1
Type 2 criteria for S1 response.
- c2
Type 2 criteria for S2 response.
- nRatings
Number of ratings.
- nTrials
Number of trials to simulate.
- Returns
- nR_S1, nR_S21d array-like
nR_S1 and nR_S2 response counts.